Designs and leads enterprise AWS data platforms, including lakehouse and warehouse architectures, data modeling, pipelines, governance, security, and cloud migration. The role integrates structured and unstructured data from enterprise systems, enables batch and real-time analytics, establishes architecture standards, and drives automation and CI/CD. It requires extensive AWS, data engineering, big data, SQL, Python, and cloud-native architecture experience, with responsibility for scalable, secure, and high-performance analytics solutions.
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Job Description:
Position Summary:
We are seeking an experienced AWS Data Architect to design, build, and manage scalable enterprise data platforms leveraging AWS cloud technologies. The ideal candidate will possess extensive expertise in Data Lakehouse architectures, Data Warehousing, Data Engineering, Big Data technologies, and Cloud Data Migration. This role will be responsible for defining data architecture standards, ensuring data governance, and enabling advanced analytics and business intelligence across the organization.
Key ResponsibilitiesData Architecture & Strategy
- Define and implement enterprise data architecture roadmap aligned with business objectives.
- Design scalable Data Lakehouse and Data Warehouse solutions on AWS.
- Establish data modeling standards, architecture frameworks, and best practices.
- Develop data integration strategies for structured, semi-structured, and unstructured datasets.
- Collaborate with business stakeholders, analytics teams, and IT leadership to deliver data-driven solutions.
- Architect end-to-end data solutions using AWS services
- Design secure and high-performing cloud-native data platforms.
- Optimize data storage, data processing, and query performance.
- Implement modern Lakehouse architectures using technologies such as:
- Databricks
- Delta Lake
- Apache Iceberg
- Apache Hudi
- Design dimensional and enterprise data warehouse models.
- Create scalable ETL/ELT frameworks to support analytics and reporting requirements.
- Enable real-time and batch data processing capabilities.
- Implement data governance, metadata management, lineage, and data quality frameworks.
- Ensure compliance with security and regulatory requirements.
- Define role-based access controls and data protection strategies.
- Partner with cybersecurity teams to maintain data security standards.
- Design and oversee enterprise data pipelines.
- Lead cloud migration initiatives from legacy on-premise platforms to AWS.
- Integrate ERP, CRM, eCommerce, supply chain, finance, and third-party systems.
- Drive automation and CI/CD practices for data platform deployments.
- Bachelor's or master's degree in engineering, or related field.
- 10+ years of experience in Data Architecture, Data Engineering, or Data Platform Management.
- 5+ years of experience in AWS cloud-based data solutions.
- Strong expertise in:
- Data Lakehouse Architecture
- Enterprise Data Warehouse Design
- Data Modeling (Dimensional & Data Vault)
- ETL/ELT Frameworks
- Big Data Technologies
- Hands-on experience with SQL and Python.
- Strong understanding of cloud-native architecture principles.
- Amazon S3
- AWS Glue
- AWS Lake Formation
- Amazon Redshift
- Amazon Athena
- Amazon EMR
- AWS Lambda
- Amazon Kinesis
- AWS IAM
- AWS CloudFormation/Terraform
- Snowflake
- Amazon Redshift
- PostgreSQL
- SQL Server
- Oracle
- MySQL
- Databricks
- Delta Lake
- Apache Spark
- Apache Iceberg
- Apache Hudi
- AWS Certified Solutions Architect – Professional
- AWS Certified Data Engineer – Associate
- AWS Certified Data Analytics – Specialty
- Databricks Certified Data Engineer
- Snowflake Certification
Ideal Candidate: An AWS Data Architect who can lead data modernization initiatives, drive Data Lakehouse adoption, and deliver scalable, secure, and high-performance analytics platforms supporting business growth and digital transformation.
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